DataFrame vs Series
Series |
DataFrame |
|---|---|
|
One- dimensional |
Two- dimensional |
|
Series elements must be homogenous. |
Can be heterogeneous. |
|
Immutable(size cannot be changed). |
Mutable(size can be changeable). |
|
Element wise computations. |
Column wise computations. |
|
Functionality is less. |
Functionality is more. |
|
Alignment not supported. |
Alignment is supported. |
DataFrame vs Series in Pandas
Pandas is a widely-used Python library for data analysis that provides two essential data structures: Series and DataFrame. These structures are potent tools for handling and examining data, but they have different features and applications.
In this article, we will explore the differences between Series and DataFrames.
Table of Content
- What are pandas?
- What is the Pandas series?
- Key Features of Series data structure:
- What is Pandas Dataframe?
- Key Features of Data Frame data structures:
- DataFrame vs Series